With the advent and development of new sensor technologies, it is now possible to capture image data in tens or hundreds of wavelength-resolved bands covering a broad spectral range. Compared to traditional monochrome and trichromatic cameras, hyperspectral image sensors provide an information-rich representation of the spectral response for the material under study over a number of wavelengths. This has opened-up great opportunities and posed important challenges due to the high dimensional nature of the spectral data.
The use of local image descriptors opens-up great opportunities in recognition and classification tasks. Moreover, the multidimensional nature of local image features and descriptors may be combined to improve performance.
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